The present invention relates to a processing device, a processing method, an information storage device, and the like.
In medical sites, a physician acquires a tissue image of a patient (subject), and checks the acquired tissue image to determine whether or not there is an abnormality in a tissue. The number of tissue images acquired might be extremely large, requiring the physician to take a long time to check all of the images.
Thus, in recent years, studies have been made on a processing device for supporting the physician, in diagnosis, by checking and identifying the contents of a great number of tissue images one by one to automatically identify a tissue image including a portion with abnormality and presenting the tissue image to the physician. This automatic identification of the contents of the images is performed as follows. Specifically, an identification criterion is generated in advance through machine learning using learning images provided with true labels in advance. In this condition, the contents of the images acquired by the physician for diagnosis are mechanically identified with the identification criterion, and an identification result is presented to the physician and the like.
The identification criterion is preferably usable for identifying rare cases. In this context, studies have been made on a method including performing successive learning by using images actually acquired in the medical site to update the identification criterion prepared in advance to increase identifiable cases. The mechanical learning for updating the original identification criterion by using new learning data appended with a corrected label is referred to as incremental learning. JP-A-2009-37565 discloses an invention that is a conventional technique related to the incremental learning.